Udemy
    •  
    •  
    •  
    •  
    •  
    •  
    •  
    •  
Turn what you know into an opportunity and reach millions around the world.
Learn More
Your cart is empty.
Keep shopping
Data Quality Essentials: A Crash Course
Rating: 4.9 out of 5(5 ratings)
287 students

Data Quality Essentials: A Crash Course

Step into data quality management!
Created byKieran Keene
Last updated 11/2023
English
English [Auto],

What you'll learn

  • Essentials of data quality
  • Processes, technical changes & organisational changes related to data quality
  • How to identify data quality issues
  • How to monitor data quality issues

Course content

4 sections11 lectures1h 0m total length
  • Introduction6:06

    Explore how data quality reflects the real world, covering accuracy, completeness, consistency, timeliness, relevance, and uniqueness, and learn how poor quality harms decisions, resources, and revenue.

  • The 6 dimensions of quality17:20

    Explore the six dimensions of data quality—accuracy, completeness, consistency, timeliness, relevance, and uniqueness—and apply data validation, audits, profiling, and governance to improve data reliability and actionable insights.

Requirements

  • None

Description

This course is designed to equip participants with the knowledge and tools necessary to understand, evaluate, and enhance the quality of data within organisational contexts. In today's data-driven world, the significance of reliable, accurate, and high-quality data cannot be overstated.

The course is not designed to make you an expert but rather to give you a good grounding in data quality, it's importance and to give you some actionable steps to take after the course.

Throughout this course, participants will delve into the fundamental concepts of data quality, exploring its definition and significance in various operational and analytical contexts.

Participants will learn practical methodologies and tools for assessing data quality within their organisations and then delve into strategies for enhancing data quality, covering both process-oriented changes and organisational shifts necessary to establish a culture of data quality improvement.

We'll look at utilising data pipelines to improve and monitor data quality.

No previous experience is required. By the end of this course you should have a good understanding of some of the steps we can take to improve and monitor data quality.

Join me on this exciting journey towards mastering data quality management and unleash the potential of your data assets.

Who this course is for:

  • Individuals who have an interest in ensuring data is high quality